The present invention generally relates to windfarms, and more specifically to a method for designing the layout of turbines in a windfarm.
The layout of turbines in a windfarm influences the total amount of power produced by the windfarm. Prior art wind farm layouts are often a simple checkerboard design where turbines are placed a fixed number of diameters apart in one direction and a different fixed number of diameters apart in the perpendicular direction. This is done to minimize the wake interaction effects by maximally separating turbines on the farm. However, the simple checkerboard design is often very conservative and hence leads to very large land use for a given set of turbines. Therefore, the checkerboard design is not often the optimal layout design.
Alternate designs use heuristic methods to design the layout, often leading to designs that have sub-optimal energy yield for a given farm. Most of the existing prior art works that address turbine layout while incorporating wake interaction effects use incomplete heuristic methods. Such methods do not guarantee optimality of the layout solution, and further do not provide a bound on the gap between the best layout found and the optimal layout.
In one reference of the prior art on turbine layout design, the wind farm is divided into a square grid and the center of each grid cell becomes a potential placement location. A genetic algorithm is used to minimize a weighted sum of wind energy and turbine costs. In this context, the genetic algorithm is a solution method where a population of candidate turbine layouts is maintained, and the layouts are evolved into new candidate layouts through mutation and crossover procedures. Another prior art study discloses solution techniques to minimize the cost of energy of a wind farm specified as the total expenditure divided by the total energy produced by the farm. These methods do not necessarily guarantee the optimality of the turbine layout.
Thus, there is a need in the art for a method for designing the layout of turbines in a windfarm that accounts for the nonlinear wake effects and interactions between the turbines to maximize the amount of power (energy yield) from a windfarm site and minimizes the land use for a given power output.